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While this is a utopian perspective of the future of AI, let's consider another example - an AI-enabled self-driving car runs over a woman trying to cross the road, claiming her life. Although the driver is in the car, AI was in full control. In this scenario, who is to be held responsible for the death of the woman? The manufacturers of the onboard sensory equipment; Designer of the AI system or the person behind the wheel! AI allows machines to 'learn' from data and make decisions, without being explicitly programmed.

Today, data is the bread and butter of the IT world. We feed the huge amounts of data to the analytics tool and expect information and insights in return. These insights and information help us take business decisions and predict future outcomes of several new processes, products, and procedures.

Now, we already use these technologies in our day-to-day lives. Think of Alexa, Google Home, and Siri. All these personal assistants are developed using the concepts of artificial intelligence and machine learning. While these are still extreme examples of months of hard work, we have simpler implementations of AI and ML too. Amazon's recommendation bar, for instance. Based on your buying patterns and recent searches, Amazon creates a recommended list for you to find what you are looking for sooner than later.